Impact of MGNREGS on poverty in Andhra Pradesh: A case study

American International Journal of Research in Humanities, Arts and Social Sciences Available online at http://www.iasir.net ISSN (Print): 2328-3734, ISSN (Online): 2328-3696, ISSN (CD-ROM): 2328-3688 AIJRHASS is a refereed, indexed, peer-reviewed, multidisciplinary and open access journal published by International Association of Scientific Innovation and Research (IASIR), USA (An Association Unifying the Sciences, Engineering, and Applied Research) Impact of MGNREGS on poverty in Andhra Pradesh: A case study Dr. Ch. V. Krishna Reddy Doctoral Fellow, ICSSR, Dept. of Commerce and Business Administration, Achrya Nagarjuna University, Guntur, A.P., INDIA. Abstract: Agricultural wage earners, small and marginal farmers and casual workers engaged in nonagricultural activities, constitute the bulk of the rural poor in India. Small land holdings and their low productivity are the cause of poverty among households dependent on land-based activities for their livelihood. Poor educational base and lack of other vocational skills also perpetuate poverty. Due to the poor physical and social capital base, a large proportion of the people are forced to seek employment in vocations with extremely low levels of productivity and wages. A developing economy like India is often characterised by a labour market with demand and supply of labour and a wage that even if competitively determined may not be adequate for the poor household to reach their target income; what they consider as means of a decent living. Proper utilization of both human and material resources was the major challenges for the economic development of Independent India. At the time of its independence, the country had low level of economic and technological development, low per capital income, slow pace of development of economic and social institutions and outdated production techniques. The objective of the Independent India was to attain and accelerate the economic development of the country. Hence, the Planning Commission of India was established in 1950 to accelerate the economic development and to raise the standard of living of the people through systematic utilization of the resources of the country, increasing production and providing opportunities to all. The Planning Commission formulate the plans for the most effective and balanced utilization of country s resources by determining priorities. The main focus of the planning commission since its inception was rural development. So far, numerous programmes proposed by planning commission have been taken up by government of India to address the problems of rural unemployment and rural poverty. I. Timeline of Wage employment programmes in India The measures taken by the Planning Commission till 1972 to provide employment for rural labour are: 1) Land Reclamation Scheme, 2) Integrated Area Development Scheme and 3) The Employee s State Insurance Scheme. Maharashtra was the first Indian state which has announced an employment generating scheme based on a right to livelihood approach in 1972-73. 1980: National rural employment programme: The National Rural Employment Programme (NREP) was started in 1980. 1983: Rural landless employment guarantee programme: To this was added the Rural Landless Employment Guarantee Programme (RLEGP) in 1983. 1989: Jawahar rozgar yojana: The NREP and RLEGP were merged in April 1989 under the Jawahar Rozgar Yojana (JRY). The JRY was meant to generate meaningful employment opportunities for the unemployed and underemployed in rural areas through the creation of economic infrastructure and community and social assets. 1993: Employment assurance scheme: The Employment Assurance Scheme (EAS) was launched on 2 October 1993 covering 1,778 drought-prone, desert and tribal and hill area blocks. It was later extended to all the blocks in 1997-98. The EAS was designed to provide employment in the form of manual work in the lean agricultural season. 1999: Jawahar gram samridhi yojana: The JRY was revamped from 1 April 1999 as the Jawahar Gram Samridhi Yojana (JGSY). It now became a programme for the creation of rural economic infrastructure with employment generation as a secondary objective. The Programme is implemented by the village panchayats and provides for specific benefits to SC/STs, the disabled and the maintenance of community assets created in the past. 2001: Sampoorna grameen rozgar yojana: The Sampoorna Grameen Rozgar Yojana (SGRY) was launched on 25 September, 2001 by merging the on-going schemes of EAS and the JGSY with the objective of providing additional wage employment and food security, alongside creation of durable community assets in rural areas. The Programme is self-targeting in nature with provisions for special emphasis on women, scheduled castes, AIJRHASS 16-320; 2016, AIJRHASS All Rights Reserved Page 80

scheduled tribes and parents of children withdrawn from hazardous occupations. The Centre and the states share the cost of the cash component of the scheme in the ratio of 75:25 2004: National food for work programme: The Food for Work Programme was started in 2000-01 as a component of the EAS in eight notified drought-affected states of Chhattisgarh, Gujarat, Himachal Pradesh, Madhya Pradesh, Orissa, Rajasthan, Maharashtra and Uttaranchal. 2005: Ensuring a minimum level of livelihood security in the rural areas has been one of the daunting tasks for successive governments. Evolving the design of the wage employment programmes to more effectively fight poverty, the Central Government formulated the National Rural Employment Guarantee Act (NREGA). 2006: 'National Rural Employment Guarantee Act' 2005 (NREGA) was launched with effect from 2nd February 2006. 2009-10: through an amendment the NREGA has been rechristened as the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA). The potential of NREGA spans a range of possibilities. II. MGNREGA-Andhra Pradesh Andhra Pradesh s share of total participating households at national level was 10.3 per cent in 2006-07 and it increased to 11.5 per cent in 2010-11. The share of ST households in employment increased from 13.58 per cent to 15 per cent during same period owing to improved reach of the Program to interior villages. The share of women participation in the state (54%) was moderately higher than that of national level average as well as share of male workers in the state. Of the total available funds of Rs.155,298.33 crore at the national level, Andhra Pradesh has alone spent 10.094 per cent during the last five years and generated more than 122 crore person-days of employment by executing 15.05 lakh works and an average of about 58 per cent of available funds utilized by the state. The share of expenditure on material has increased from 1.76 per cent in 2006-07 to 30.5-4 per cent in 2011-12, as the state has allocating 25 per cent funds towards rural connectivity works. MGNREGA is expected to change the whole rural scenario. And there is no doubt that its promise has ignited the hearts and minds of the rural poor with unprecedented hopes and expectations. But the program have also shown that MGNREGA suffers from many drawbacks, leakages and delays in wage payments, non-payment of statutory minimum wages, work only for an average of 50 days per annum as against the promised 100 days, fudged muster rolls, few durable assets and even fewer sustainable livelihoods. III. Need for the study and objective of the study Direct provision of wage employment is obviously an attractive instrument for poverty alleviation wherever the poor depend heavily upon wage employment for their income and also suffer from considerable unemployment and underemployment. Wage employment Programmes have sought to achieve multiple objectives. They not only provide employment opportunities but ultimately provide food security of the poor. Several studies have shown that MGNREGS is reaching the poor and socially and economically backward sections. There is no uniform opinion among the scholars and authors on MGNREGA. Some are positive and some are negative. Many scholars mention different works taken up by the Scheme but they did not explain the sustainability of those works. In this regard the study is proposed to estimate the impact of MGNREGS days on level of deprivation and it s determinants in Andhra Pradesh. IV. Research methodology A purposive sampling method was employed for the selection of the study districts. In the first stage Andhra Pradesh is divided into two regions which are costal Andhra and Rayalaseema regions. In the second stage one district was selected from each region on the basis of high performance in providing work days under the MGNREGS, they were Prakasam district from Costal Andhra region and Anantapur district from Rayalaseema regions. In the third stage one mandal was selected from the above selected districts on the performance basis. In the fourth stage two villages which provided high employment person days were selected from each mandal. It was decided to select a sample of 128 farm households. A detailed and well structured questionnaire was used to elicit the information from the farm households. For data analysis descriptive statistics, percentages and logistic regression analyses are used to estimate the impact of MGNREGS days on level of deprivation. It can be inferred that a state of deprivation for the selected indicators is found among households irrespective of social status. V. Socio Economics Variables Access to civic facilities for the MNREGS households is presented in table-1. Among the respondents only 42 per cent of the respondents have gas connections, 67 per cent have drinking water facility at their house premises and all most all the households of all the communities are provided with electricity connection. Drainage facility is one of the development indicators; it helps for the clean environment for the respondents. Only 32 per cent of the households have drainage facility. This clearly indicates that the depravation of civic facilities among the households. Only 34.64 per cent of BC s, 46.67 per cent of OC s, 24.32 per cent of SC s, AIJRHASS 16-320; 2016, AIJRHASS All Rights Reserved Page 81

21.54 per cent of ST s have drainage facility. This should be improved for better health conditions of the people. Roads are the better means of transport. Among the respondents 67.22 per cent have drinking water facility. Among BC s 70.95 percent, among OC s 80, SC s 59.46 and ST s 58.46 per cent of households have drinking water facility at their house premise. This shows that the existing water facilities are not sufficient in almost all caste categories. For better living durable goods are required for families. They are also considered as assets for understanding the social and economic efficiency of the households. It is observed that among the respondents 62 per cent of the respondents have Televisions in their houses. The forward and backward community respondents had more gas connections than other communities. About 74 per cent of households have fans. One interesting thing is that the usage of mobiles is 70 percent. Among the sample households, 31.69 per cent had motor bikes. Table-1 Socio Economics Variables (Percentages) BC OC SC ST Total Pucca 70.39 86.67 82.43 98.46 84.49 Gas 42.46 63.33 28.38 33.85 42.00 Electricity 92.18 90.00 93.24 96.92 93.09 Drinking water 70.95 80.00 59.46 58.46 67.22 Drainage 34.64 46.67 24.32 21.54 31.79 Latrine 31.84 60.00 36.49 36.92 41.31 Road facility 64.80 73.33 85.14 75.38 74.66 TV 54.19 76.67 62.16 55.38 62.10 L.P.G. 35.75 63.33 20.27 27.69 36.76 Fan 76.54 83.33 66.22 69.23 73.83 Motor Cycle 20.11 50.00 24.32 32.31 31.69 Mobile 58.10 76.67 71.62 75.38 70.44 Source: Primary Data. Note: Percentage to the respective total. Note: O.C- Socially, Economically Forward cast communities and other castes. B.C- Socially, Economically Backward cast communities. S.C- Scheduled caste communities. S.T- Scheduled Tribe communities. VI. Index of Deprivation (ID) A simple index of deprivation is computed by taking the sum of total of all such scores. The indicators which show significant difference between poor and non- poor in their levels of living are used in computing deprivation index. The entire variables include computing deprivation index for giving equal weight and categorized as deprived and non-deprived. The score 1 is assigned to identify the socio economic variables if the household did not enjoy the social and economic benefit or status in the society. Otherwise zero score is assigned. The ID value ranges from 0 to 12. If the household sets a value 0, it indicates that the household has not been deprived in any of the ten aspects. If the household gets a value 12, then the household is considered to be deprived of in all aspects. The index of deprivation for the identified variables has been computed for each of the individual households which is presented in table-2. ID value ranges between 0 to 12. The percentage distribution of households by the level of deprivation is categorized as not deprived (0-2), less deprived (3-5), and more deprived (6-8) and most deprived (9-12). It could be observed from the table, that 73 per cent of the households are in deprived state and only 4.72 per cent of the households are in a not deprived state and the remaining 20.47 per cent of the households are in a less deprived state. The most deprived households whose ID value ranges between 9-12 account for 40.94 per cent of the total households. About 58 percent and 60 percent of scheduled tribe and scheduled caste category households are in most deprived status. However in the case of Backward caste category and forward castes it is 31 percent and 20 percent respectively. Intra caste category comparison shows that as the caste category decreases the percentage of most deprived status increasing. The remaining scheduled cast and scheduled tribe households are in less deprived status. And there is a positive relationship is observed among less deprived households. Nearly 26 per cent of backward caste households and 30 per cent of forward cast are in less deprived status. Whereas, in the case of schedule tribes and schedule castes nearly 8 percent and 12 percent respectively are in the less deprived status. There is not even a scheduled cast household which is in not deprived status. It can be inferred that a state of deprivation for the selected indicators is found among households irrespective of social status. However the state of deprivation is found to be more among scheduled caste and scheduled tribe household categories when compared to other corresponding categories households. AIJRHASS 16-320; 2016, AIJRHASS All Rights Reserved Page 82

Table -2 Distribution of households by level of deprivation Sl. Range of ID Schedule Schedule Backward Forward Total No tribes casts casts casts 1 Not Deprived (0-2) 2 0 3 2 7 (8.33) (0.00) (4.41) (10.00) (4.72) 2 Less deprived (3-5) 2 3 18 3 26 (8.33) (12.00) (26.47) (30.00) (20.47) 3 Moderately deprived (6-8) 6 7 26 4 43 (25.00) (28.00) (38.24) (40.00) (33.86) 4 Most deprived (9-12) 14 15 21 2 52 (58.33) (60.00) (30.88) (20.00) (40.94) 5 Total 24 25 68 11 128 (100.00) (100.00) (100.00) (100.00) (100.00) Source: Primary data. Note: Figures in parentheses represent percentages to respective total. VII. Estimation of the Logit Model Within the logit framework this study has postulated that the probability of an individual being poor (P i) is dependent upon the attributes like age, Number of litterates, land size, social status, Number of earners in the household, household income and man-days employed. The index variable P i indicating whether the respondent is poor or non-poor has been expressed as a linear function of the independent variables. Thus, the logit regression model has been specified as follows. P i = i+ 1X 1+ 2X 2+ 3X 3+ 4X 4+ 5X 5+ 6X 6+u i Where, P i - level of deprivation (1-Deprived, 0-Not deprived) X 1 - Number of literates in the household, X 2 - Social status of the households; 1 if scheduled caste or tribe; 0, otherwise, X 3 - family size of the household, X 4 - Man-days of MGNREGS employment of the household, X 5 - Number of earners in the household, X 6 - Annual income of the household in rupees, i s - Parameters to be estimated, u i - Error term. VIII. MLE Coefficient for logit model The maximum livelihood estimates of co-efficient of logit model for the respondent is presented in the table-3. The results of the specified logit model shows that the coefficient associations with the explanatory variables have registered an expected sign.. It could be noted from table-3 that the specified logit model was significant at 1 per cent level of probability. The level of count egested R 2 obtained was 0.761; which showed that 76 percent of the variations in the level of deprivation were explained by the changes in the explanatory variables. The result indicates that the number of literates, mandays of employment and annual income are found to be negative and significant. This indicates that the negative slope of coefficient of these variables would decrease the probability of household being deprived by their appropriative percentages (4.7 and 8.3 Percent respectively). Among the coefficient of the other explanatory variables family size is positive and significant, which indicates that the positive slope in the family size would increase the probability of respondent to be poor. And number of earners in the family is also positive but it is not significant. Table -3 MLE Coefficient for Logit model Variables Logit MLE Coefficient P i Intercept 4.5601*** X 1 Number of literates -0.0475** X 2 Social status -0.2058*** X 3 Family size 0.0228*** X 4 Man days of MGNREGS employment -0.0820*** X 5 Number of earners 0.0023* X 6 Annual Income -0.0628** R 2 0.761 Number of observers 128 Source: Primary data Note: *, **, and *** show significant at 10 percent, 5 per cent and 1 per cent level respectively AIJRHASS 16-320; 2016, AIJRHASS All Rights Reserved Page 83

Among all variables the coefficient of social status was negative and significant. This indicates that negative slope in the social status of respondents would increase the probability of households to be deprived. Hence the results reveal that the social status of the households have a great influence on their probability of being deprived. The coefficient of the other variable man days of employment under MGNREGA is negative and not significant, which indicate that the increase in the man days of employment under MGNREGA could not decrease the probability of the household to be poor significantly. IX. Conclusion MGNREGA is expected to change the whole rural economic scenario since its introduction in India. The study is proposed to estimate the impact of MGNREGS days on level of deprivation and it s determinants in Andhra Pradesh. A purposive sampling method was employed for the selection of the study districts. It was decided to select a sample of 128 farm households. For data analysis is descriptive statistics, percentages and logistic regression analyses are used. It can be inferred that a state of deprivation for the selected indicators is found among households irrespective of social status. However the state of deprivation is found to be more among scheduled caste and scheduled tribe household categories when compared to other corresponding categories households. A simple index of deprivation is computed by taking the sum of total of all such scores. About 58 percent and 60 percent of scheduled tribe and scheduled caste category households are in most deprived status. However in the case of Backward caste category and forward castes it is 31 percent and 20 percent respectively. The state of deprivation is found to be more among scheduled caste and scheduled tribe household categories when compared to other corresponding categories households. Among the respondents only 42 per cent of the respondents have gas connections, 67 per cent have drinking water facility at their house premises and all most all the households of all the communities are provided with electricity connection. Drainage facility is one of the development indicators; it helps for the clean environment for the respondents. Only 32 per cent of the households have drainage facility. Among the respondents 67.22 per cent have drinking water facility. Among the respondents 62 per cent of the respondents have Televisions in their houses. The forward and backward community respondents had more gas connections than other communities. The specified logit model was significant at 1 per cent level of probability. The level of count egested R 2 obtained was 0.761; which showed that 76 percent of the variations in the level of deprivation were explained by the changes in the explanatory variables. The result indicates that the number of literates, mandays of employment and annual income are found to be negative and significant. This indicates that negative slope of coefficient of these variables would decrease the probability of household being deprived by their appropriative percentages. The analysis clearly reveals that the Mahatma Gandhi National Rural Employment Guarantee Schemes bring expected changes in socio-economic status in rural economy. References [1] K.Hanumanta Rao and P.Durgaprasad, Rural Poverty Alleviation in India: Contribution of NREGS, IASSI Quarterly, Vol.27.Nos.1&2, 2008. [2] Prattoy Sarkar, Jagdish Kumar and Supriya, Impact of MGNREGA on Reducing Rural Poverty and Improving Socioeconomic Status of Rural Poor: A Study in Burdwan District of West Bengal, Agricultural Economics Research Review, Vol. 24 (Conference Number) 2011 pp 437-448. [3] Indira Bishnoi, Sarita Verma and Swati Rai, MNREGA: An Initiative towards Poverty Alleviation through Employment Generation, Indian Research Journal of Extension Education Special Issue (Volume I), January, 2012. [4] N.C. Saxena, Rural poverty reduction through centrally sponsored schemes INDIAN J MED RES, OCTOBER 2007, pp 381-389. AIJRHASS 16-320; 2016, AIJRHASS All Rights Reserved Page 84